R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed by John Chambers. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control. The Alison free online course “R for Data Analysis“, provides an introduction to data manipulation in R programming. This will be of great interest to professionals working in the areas of data science and data analysis and who want to learn more about using R for statistical computing.
R for Data Analysis Couse Content
This course teaches what data manipulation is and the packages or library you need to add to your program for data manipulation. You will also learn the difference between feature and observation manipulation. You will learn about grouping and how that can organize your data output.
- The libraries/packages you will need to include in your program for data manipulation;
- The process of features and observation manipulation;
- How the forward pipe operator helps cleans up and organize your code;
- What data visualization is and the difference between its two types;
- Libraries you will need to include in your r program to create visualizations;
- How to display your data on a visualization.
The learner will need the have completed the previous course “Introduction to R for Data Science“. The learner will need some knowledge of programming languages.
Summary of Main Course Features
- Duration: 2-3 Hours
- Publisher: Channel 9
- Assessments: Yes
- Certification: Yes
- Minimum Grade/Class Level: Third Level